• Title/Summary/Keyword: Principle of vehicle detecting

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Development of the autnomous road vehicle (무인 자동차 개발 연구)

  • 최진욱;한민홍
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.88-93
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    • 1993
  • This paper introduces an ARV(Autonomous Road Vehicle) system which can run on orads without help of a driver by detecting road boundaries through computer vision. This vehicle can also detect obstacles in front through sonar sensors and infrared sensors. This system largely consists of a handle steering module and a braking module. From road boundaries, the steering module determines handle turn angle. The braking module stops or decelerates to avoid collision depending on the relative speeds and distance to the obstacles detected by different sensors. This ARV system has been implemented in a small jeep and can run 30-40 km/h city traffic. In this paper, we illustrate the structure of the ARV systems and its operation principle.

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The Concept of Parking/Moving Vehicle Discrimination by Three-Line Scanner Imagery

  • Puntavungkour, Sompoch;Shibasaki, Ryosuke
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1427-1429
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    • 2003
  • In our contribution, the new idea of parking/moving discrimination is proposed by using Three Line Scanner Imagery. The framework of our study consists of three main stages: preprocessing, vehicle detection and parking/moving detection respectively. First two stages of framework have been done in our previous work. Parking/ Moving Discrimination algorithm have been developed by using generic vehicle characteristics and some principle of photogrammetry. By using detected vehicles from our previous work, stopping/moving vehicles are able to discriminate. Moving vehicle is detected by detecting generic moving vehicle in TLS, inter-band gap. Stopping vehicle is verified by 3 dimensional viewing of Stereoscopic measurement. Finally, the conceptual framework has been done and the result will been realized soon.

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Wireless Traffic Light using Artificial Intelligence

  • Hong, You-Sik;Kim, Chong-Soo;Kim, Chang-Kyun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.251-257
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    • 2003
  • In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic Intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not consider emergency vehicles for safety escort.

Wireless Traffic Signal Light using Fuzzy Rules

  • Hong YouSik;Lu Wei-Ming;Yi JaeYoung;Yi CheonHee
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.365-370
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    • 2004
  • In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not considering emergency vehicles for safety escort.

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Evaluation of a Traffic Noise Predictive Model for an Active Noise Cancellation (ANC) System (능동형 소음저감 기법을 위한 도로교통소음 예측 모형 평가 연구)

  • An, Deok Soon;Mun, Sung Ho;An, Oh Seong;Kim, Do Wan
    • International Journal of Highway Engineering
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    • v.17 no.6
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    • pp.11-18
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    • 2015
  • PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

Driver Assistance System for Integration Interpretation of Driver's Gaze and Selective Attention Model (운전자 시선 및 선택적 주의 집중 모델 통합 해석을 통한 운전자 보조 시스템)

  • Kim, Jihun;Jo, Hyunrae;Jang, Giljin;Lee, Minho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.3
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    • pp.115-122
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    • 2016
  • This paper proposes a system to detect driver's cognitive state by internal and external information of vehicle. The proposed system can measure driver's eye gaze. This is done by concept of information delivery and mutual information measure. For this study, we set up two web-cameras at vehicles to obtain visual information of the driver and front of the vehicle. We propose Gestalt principle based selective attention model to define information quantity of road scene. The saliency map based on gestalt principle is prominently represented by stimulus such as traffic signals. The proposed system assumes driver's cognitive resource allocation on the front scene by gaze analysis and head pose direction information. Then we use several feature algorithms for detecting driver's characteristics in real time. Modified census transform (MCT) based Adaboost is used to detect driver's face and its component whereas POSIT algorithms are used for eye detection and 3D head pose estimation. Experimental results show that the proposed system works well in real environment and confirm its usability.